Graphistry for Data Scientists

Smart Insights With GPU Scale

Graphs surface the nature of clusters, patterns, relationships, outliers, progressions, and other topics that are often hidden within tabular views like lists and bar charts. With Graphistry’s unique GPU acceleration in the client and cloud, you can quickly explore 10-100X more data that other systems, so that you see the whole picture instead of subsets.

Graphistry Visualization Built In to Notebook

Work Directly With Your Data and Environment

Call the PyGraphistry library directly from Jupyter and other popular Python data science environments like DataBricks. The Pandas-based API makes it easy to load data from CSVs, Spark, SQL, graph databases, and more. Directly load your own data tables and graphs. If you have custom analytics, you can annotate the data with their output, and explore the result with Graphistry.

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Built-in Components and Visual Querying

Graphistry provides a growing suite of pre-integrated direct visual interactions, collaboration tools, and charting components. For example, no more manually coding filters and plotting static bar charts of the results. Instead, visually drill down in Graphistry and open a pre-wired histogram.

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Share Insights as Executable Views

Graphistry results get shared in a variety of ways. Sometimes, that means simply exporting the CSV to Excel. Other times, it helps to report with beautiful screenshots and impressive interactive visualizations. When working with other analysts, pass around notebooks with embedded interactive Graphistry plots, or share a live URL of the Graphistry session itself. Over time, start enabling the rest of your organization to use your techniques by embedding live data views in your dashboards, or use the investigation template system and developer APIs to quickly make full interactive applications.